Applied Multivariate Analysis
Multivariate statistical methods and their use in empirical research. Topics include: summarization and visualization of multivariate data, the multivariate normal distribution, tests on mean vectors, multivariate paired comparisons, multivariate analysis of variance, repeated measures designs, test on covariance matrices, discriminant analysis and classification, canonical correlation, principal components, factor analysis and cluster analysis. Maximum likelihood estimation and the likelihood ratio method of test construction.
Topics
- summarization and visualization of multivariate data
- the multivariate normal distribution
- tests on mean vectors
- multivariate paired comparisons
- multivariate analysis of variance
- repeated measures designs
- test on covariance matrices
- discriminant analysis and classification
- canonical correlation
- principal components
- factor analysis and cluster analysis
Topics explicitly listed in official catalogue description
Prerequisites & course information
Recommended: BMGT836 or equivalent course. BMGT837 assumes working knowledge of matrices and elementary linear algebra and a sound understanding of univariate statistics, including random variables, statistical inference, ANOVA, and ordinary least squares regression.
Sources
- Course catalogue ↗2026-2027